Managers of activities such as, by way of example and not by way of limitation, call center activities which receive a high volume of voice calls may face a continual challenge to extract actionable information from large volumes of voice communications traffic. Such call center activities may include, by way of further example and not by way of limitation, retail customer service call centers, national or regional call centers related to customer-service industry businesses, or governmental agencies involved in intelligence-gathering activity. Call center activities may receive a vast number of calls that contain huge amounts of potentially important and actionable data. These activities do not currently have a way to easily identify types of calls that require timely notification of managers. Typical call center employees or supervisors may be unable to timely present critical voice call categorization data to managers because (1) too many calls containing too much data preclude rapid analysis of which calls are of immediate importance and which calls can be recorded for later handling, (2) call specifics are incomplete or not understandable and indicators such as tone or voice speed are available but are difficult to characterize, or (3) voice patterns or language in the voice call that relate to management priorities are not easy to identify.
There is a need for an apparatus and method for evaluating audio communications that can enhance pattern recognition and other historical perspective understanding of call contents to permit improved call handling.